DP-203 Design and implement data storage Practice Question
This DP-203 practice question tests your understanding of design and implement data storage. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Exhibit
Refer to the exhibit.
CREATE EXTERNAL DATA SOURCE MyDataSource
WITH (
LOCATION = 'abfss://container@storageaccount.dfs.core.windows.net',
TYPE = HADOOP,
CREDENTIAL = MyCredential
);
CREATE EXTERNAL FILE FORMAT ParquetFormat
WITH (
FORMAT_TYPE = PARQUET,
DATA_COMPRESSION = 'org.apache.hadoop.io.compress.SnappyCodec'
);
CREATE EXTERNAL TABLE dbo.Sales
(
SaleID INT,
ProductID INT,
Quantity INT,
SaleDate DATE
)
WITH (
LOCATION = '/sales/',
DATA_SOURCE = MyDataSource,
FILE_FORMAT = ParquetFormat
);
Refer to the exhibit. A data engineer creates an external table in Azure Synapse Serverless SQL. Which statement about this table is correct?
Exhibit
Refer to the exhibit.
CREATE EXTERNAL DATA SOURCE MyDataSource
WITH (
LOCATION = 'abfss://container@storageaccount.dfs.core.windows.net',
TYPE = HADOOP,
CREDENTIAL = MyCredential
);
CREATE EXTERNAL FILE FORMAT ParquetFormat
WITH (
FORMAT_TYPE = PARQUET,
DATA_COMPRESSION = 'org.apache.hadoop.io.compress.SnappyCodec'
);
CREATE EXTERNAL TABLE dbo.Sales
(
SaleID INT,
ProductID INT,
Quantity INT,
SaleDate DATE
)
WITH (
LOCATION = '/sales/',
DATA_SOURCE = MyDataSource,
FILE_FORMAT = ParquetFormat
);
A
The table supports indexing for performance
Why wrong: External tables in serverless SQL do not support indexes.
B
The external data source TYPE must be 'HADOOP' for Azure Data Lake Storage Gen2
Why wrong: TYPE=HADOOP is acceptable; it's not incorrect.
C
The table references a single Parquet file named 'Sales.parquet'
Why wrong: LOCATION='/sales/' is a folder, not a single file.
D
The table is read-only
External tables are read-only; modifications must be done to underlying files.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The table is read-only
External tables in Azure Synapse Serverless SQL are read-only because they provide a relational abstraction over data stored externally (e.g., in Azure Data Lake Storage Gen2 or Blob Storage). You cannot perform INSERT, UPDATE, DELETE, or DDL modifications on the underlying data through the external table; it is designed solely for querying with T-SQL. This is a fundamental constraint of the serverless SQL pool architecture, which uses the OPENROWSET or CREATE EXTERNAL TABLE syntax to read files in place without a storage engine.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
The table supports indexing for performance
Why it's wrong here
External tables in serverless SQL do not support indexes.
✗
The external data source TYPE must be 'HADOOP' for Azure Data Lake Storage Gen2
Why it's wrong here
TYPE=HADOOP is acceptable; it's not incorrect.
✗
The table references a single Parquet file named 'Sales.parquet'
Why it's wrong here
LOCATION='/sales/' is a folder, not a single file.
✓
The table is read-only
Why this is correct
External tables are read-only; modifications must be done to underlying files.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse external tables in Synapse Serverless SQL with external tables in dedicated SQL pools (which also support PolyBase with Hadoop connectors) and mistakenly think they can write to or index the table, or they misremember the required data source TYPE for ADLS Gen2.
Detailed technical explanation
How to think about this question
Under the hood, Synapse Serverless SQL uses a distributed query engine that pushes down filters and aggregations to the storage layer (e.g., Parquet row group pruning) but never materializes data into the SQL pool. This means external tables are ideal for data lake exploration and ELT staging where you need to query raw files without moving them, but they cannot be used for transactional workloads. A real-world scenario is using an external table to join sales data from multiple Parquet partitions (e.g., by date) with a reference table in a dedicated SQL pool, where the external table is strictly read-only.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Quick reference
Cloud Service Model Comparison
Model
You Manage
Provider Manages
Examples
IaaS
OS, runtime, apps, data
Hardware, hypervisor, networking
EC2, Azure VMs, GCP Compute Engine
PaaS
Apps and data
OS, runtime, middleware, hardware
Elastic Beanstalk, Azure App Service
SaaS
Data and settings only
Everything else
Microsoft 365, Salesforce, Workday
FaaS / Serverless
Function code only
Infra, scaling, runtime
Lambda, Azure Functions, Cloud Run
CaaS
Containers and apps
Kubernetes, OS, hardware
EKS, AKS, GKE
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-203 question in full detail.
Design and implement data storage — This question tests Design and implement data storage — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The table is read-only — External tables in Azure Synapse Serverless SQL are read-only because they provide a relational abstraction over data stored externally (e.g., in Azure Data Lake Storage Gen2 or Blob Storage). You cannot perform INSERT, UPDATE, DELETE, or DDL modifications on the underlying data through the external table; it is designed solely for querying with T-SQL. This is a fundamental constraint of the serverless SQL pool architecture, which uses the OPENROWSET or CREATE EXTERNAL TABLE syntax to read files in place without a storage engine.
What should I do if I get this DP-203 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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